def __init__(
self,
model_name='densenet-lite-gru',
model_epoch=None,
cand_alphabet=None,
root=data_dir(),
context='cpu',
name=None,
):
self._args = (model_name, model_epoch, cand_alphabet, root, context, name)
self._model_loaded = False
def init(
self,
model_name='densenet-lite-gru',
model_epoch=None,
cand_alphabet=None,
root=data_dir(),
context='cpu',
name=None,
):
"""
:param model_name: 模型名称
:param model_epoch: 模型迭代次数
:param cand_alphabet: 待识别字符所在的候选集合。默认为 `None`，表示不限定识别字符范围
:param root: 模型文件所在的根目录。
Linux/Mac下默认值为 `~/.cnocr`，表示模型文件所处文件夹类似 `~/.cnocr/1.1.0/conv-lite-fc-0027`。
Windows下默认值为 ``。
:param context: 'cpu', or 'gpu'。表明预测时是使用CPU还是GPU。默认为CPU。
:param name: 正在初始化的这个实例名称。如果需要同时初始化多个实例，需要为不同的实例指定不同的名称。
"""
check_model_name(model_name)
self._model_name = model_name
self._model_file_prefix = '{}-{}'.format(self.MODEL_FILE_PREFIX,
model_name)
self._model_epoch = model_epoch
self._model_dir = root # Change folder structure.
self._assert_and_prepare_model_files()
self._alphabet, self._inv_alph_dict = read_charset(
os.path.join(self._model_dir, 'label_cn.txt'))
self._cand_alph_idx = None
# Alphabet will be set before calling ocr.
# self.set_cand_alphabet(cand_alphabet)
self._hp = Hyperparams()
self._hp._loss_type = None # infer mode
self._hp._num_classes = len(self._alphabet)
# 传入''的话，也改成传入None
self._net_prefix = None if name == '' else name
self._mod = self._get_module(AlOcr.CNOCR_CONTEXT)